Search results for: network group behavior

Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani

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This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.

Keywords: tunnel fire, flame length, ANN, genetic algorithm

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Authors: Jiawen Wang, Qijun Chen

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The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

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Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

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Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

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Authors: Raphael Rehmet, Armin Lohrengel, Prof Dr-Ing

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In terms of making machines more silent and convenient, it is necessary to analyze the transmission path of mechanical vibrations and structure-bone noise. A typical solution for the elimination of structure-bone noise would be to simply add stiffeners or additional masses to change the transmission behavior and, thereby, avoid the propagation of vibrations. Another solution could be to use materials with a different damping behavior, such as elastomers, to isolate the machine dynamically. This research approach investigates the damping behavior of additive printed components made from structural steel or titanium, which have been manufactured in the “Laser Powder Bed Fusion“-process. By using the design flexibility which this process comes with, it will be investigated how a local impedance difference will affect the transmission behavior of the specimens.

Keywords: 3D-printed, acoustics, dynamics, impedance

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Authors: Zhidong Zhang, Yingchen Yang

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In this study, a diagnostic assessment model for Mastery Engineering Learning was established based on a group of undergraduate students who studied in an engineering course. A diagnostic assessment model can examine both students' learning process and report achievement results. One very unique characteristic is that the diagnostic assessment model can recognize the errors and anything blocking students in their learning processes. The feedback is provided to help students to know how to solve the learning problems with alternative strategies and help the instructor to find alternative pedagogical strategies in the instructional designs. Dynamics is a core course in which is a common course being shared by several engineering programs. This course is a very challenging for engineering students to solve the problems. Thus knowledge acquisition and problem-solving skills are crucial for student success. Therefore, developing an effective and valid assessment model for student learning are of great importance. Diagnostic assessment is such a model which can provide effective feedback for both students and instructor in the mastery of engineering learning.

Keywords: diagnostic assessment, mastery learning, engineering, bayesian network model, learning processes

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Authors: Mustafina-Bredikhina Diana, Kuznetsova Olga

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Corruption as a social phenomenon is obviously a serious barrier to the development of a prosperous society and the economic development of the country as a whole. It is extremely important to analyze the influence of culture on the level of corruption in different countries and assesses the influence of culture, religion, and mentality on corrupt behavior and their perception in society. Corruption should be considered in relation to the public consciousness, which is formed in certain socio-historical conditions and cultural traditions. Often, society, formally condemning corruption, reproduces obvious corrupt behavior at the personal level of its individual members. Based on a brief analysis of the major corruption scandals and the corruption counting system of countries, the authors conclude that culture, mentality, and religion, while playing an important role in the formation of public consciousness of the concept of "corrupt behavior" are not decisive. It is more important to build a dialogue between the authorities and society, creating a uniform rejection of corrupt behavior.

Keywords: corruption, culture, corrupt behavior, perception of corruption, religion

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Authors: Thilini M. Yatanwala

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CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

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Authors: Farah Al-Shatti, Elsayed El-Khamisi, Nabel Suleiman

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The study aimed at identifying the relationship between self-injury behavior and social skills among children with mild intellectual disability (ID) in the state of Kuwait. The sample of the study consisted of 65 males and females with ID; their ages ranged between 8 to 12 years. The study used a measure for rating self-injury behavior designed by the researcher; and a measure for rating social skills was designed. The results of the study showed that there was an increase in the percentages of the two dimensions of the self-injury behavior for children with ID; the self-injury behavior by child’s own body was higher than the self-injury behavior by environmental tools, additionally the results showed that there were statistically significant differences between males and females on the dimensions and total scorer of self-injury scale favor the males, and there were statistically significant differences between them on the dimensions of the social skills and total score favor the females, It also indicated that there was statistically significant negative relationship between the dimensions of the self-injury and the dimensions of the social skills for children with intellectual disability.

Keywords: mild intellectual disability, self injury behavior, social skills, state of Kuwait

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Authors: Bo Keun Lee, Doo Yeon Kwon, Ji Hoon Park, Gun Hee Lee, Ji Hye Baek, Heung Jae Chun, Young Joo Koh, Moon Suk Kim

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Thermo-responsive materials are viscoelastic materials that undergo a sol-to-gel phase transition at a specific temperature and many materials have been developed. MPEG-b-PCL (MPC) as a thermo-responsive material contained hydrophilic and hydrophobic segments and it formed an ordered crystalline structure of hydrophobic PCL segments in aqueous solutions. The ordered crystalline structure packed tightly or aggregated and finally induced an aggregated gel through intra- and inter-molecular interactions as a function of temperature. Thus, we introduced anionic and cationic groups into the end positions of the PCL chain to alter the hydrophobicity of the PCL segment. Introducing anionic and cationic groups into the PCL end position altered their solubility by changing the crystallinity and hydrophobicity of the PCL block domains. These results indicated that the properties of the end group in the hydrophobic PCL blockand the balance between hydrophobicity and hydrophilicity affect thermo-responsivebehavior of the copolymers in aqueous solutions. Thus, we concluded that determinant of the temperature-dependent thermo-responsive behavior of MPC depend on the ionic end group in the PCL block. So, we introduced zwitterionic end groups to investigate the thermo-responsive behavior of MPC. Methoxypoly(ethylene oxide) and ε-caprolactone (CL) were randomly copolymerized that introduced varying hydrophobic PCL lengths and an MPC featuring a zwitterionic sulfobetaine (MPC-ZW) at the chain end of the PCL segment. The MPC and MPC-ZW copolymers were obtained formed sol-state at room temperature when prepared as 20-wt% aqueous solutions. The solubility of MPC decreased when the PCL block was increased from molecular weight. The solubilization time of MPC-2.4k was around 20 min and MPC-2.8k, MPC-3.0k increased to 30 min and 1 h, respectively. MPC-3.6k was not solubilized. In case of MPC-ZW 3.6k, However, the zwitterion-modified MPC copolymers were solubilized in 3–5 min. This result indicates that the zwitterionic end group of the MPC-ZW diblock copolymer increased the aqueous solubility of the diblock copolymer even when the length of the hydrophobic PCL segment was increased. MPC and MPC-ZW diblock copolymers that featuring zwitterionic end groups were synthesized successfully. The sol-to-gel phase-transition was formed that specific temperature depend on the length of the PCL hydrophobic segments introduced and on the zwitterion groups attached to the MPC chain end. This result indicated that the zwitterionic end groups reduced the hydrophobicity in the PCL block and changed the solubilization. The MPC-ZW diblock copolymer can be utilized as a potential injectable drug and cell carrier.

Keywords: thermo-responsive material, zwitterionic, hydrophobic, crystallization, phase transition

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Authors: B. Manoj Kumar, C. Malavika, E. S. Kannan

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The objective of this study is to investigate the switching behavior of two vertically aligned memristors connected by a shared top electrode, a configuration that significantly deviates from the conventional single oxide layer sandwiched between two electrodes. The device is fabricated by bridging copper electrodes with mechanically exfoliated van der Waals metal (specifically tantalum disulfide and tantalum diselenide). The device demonstrates threshold-switching behavior in its I-V characteristics. When the input voltage signal is ramped with voltages below the threshold, the output current shows spiking behavior, resembling integrated and firing actions without extra circuitry. We also investigated the self-reset behavior of the device. Using a continuous constant voltage bias, we activated the device to the firing state. After removing the bias and reapplying it shortly afterward, the current returned to its initial state. This indicates that the device can spontaneously return to its resting state. The outcome of this investigation offers a fresh perspective on memristor-based device design and an efficient method to construct hardware for neuromorphic computing systems.

Keywords: integrated and firing, memristor, spiking behavior, threshold switching

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Authors: Trupti Chavan, Ramachandra Guda, Kameshwar Rao

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The lack of data is a pain problem in medical image analysis using a convolutional neural network (CNN). This work uses various spatial transformation techniques to address the medical image augmentation issue for knee detection and localization using an enhanced single shot detector (SSD) network. The spatial transforms like a negative, histogram equalization, power law, sharpening, averaging, gaussian blurring, etc. help to generate more samples, serve as pre-processing methods, and highlight the features of interest. The experimentation is done on the OpenKnee dataset which is a collection of knee images from the openly available online sources. The CNN called enhanced single shot detector (SSD) is utilized for the detection and localization of the knee joint from a given X-ray image. It is an enhanced version of the famous SSD network and is modified in such a way that it will reduce the number of prediction boxes at the output side. It consists of a classification network (VGGNET) and an auxiliary detection network. The performance is measured in mean average precision (mAP), and 99.96% mAP is achieved using the proposed enhanced SSD with spatial transformations. It is also seen that the localization boundary is comparatively more refined and closer to the ground truth in spatial augmentation and gives better detection and localization of knee joints.

Keywords: data augmentation, enhanced SSD, knee detection and localization, medical image analysis, openKnee, Spatial transformations

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Authors: Khadija Al-Hosni, Moon Fai Chan, Mohammed Al-Azri

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Background: Several studies suggest that most school-age adolescents are poorly informed on cancer warning signs and risk factors. Providing adolescents with sufficient knowledge would increase their awareness in adulthood and improve seeking behaviors later. Significant: The results will provide a clear vision in assisting key decision-makers in formulating policies on the students' awareness programs towards cancer. So, the likelihood of avoiding cancer in the future will be increased or even promote early diagnosis. Objectives: to evaluate the effectiveness of an education program designed to increase awareness of cancer signs and symptoms risk factors, improve the behavior of seeking help among school students in Oman, and address the barriers to obtaining medical help. Methods: A randomized controlled trial with two groups was conducted in Oman. A total of 1716 students (n=886/control, n= 830/education), aged 15-17 years, at 10th and 11th grade from 12 governmental schools 3 in governorates from 20-February-2022 to 12-May-2022. Basic demographic data were collected, and the Cancer Awareness Measure (CAM) was used as the primary outcome. Data were collected at baseline (T0) and 4 weeks after (T1). The intervention group received an education program about cancer's cause and its signs and symptoms. In contrast, the control group did not receive any education related to this issue during the study period. Non-parametric tests were used to compare the outcomes between groups. Results: At T0, the lamp was the most recognized cancer warning sign in the control (55.0%) and intervention (55.2%) groups. However, there were no significant changes at T1 for all signs in the control group. In contrast, all sign outcomes were improved significantly (p<0.001) in the intervention group, and the highest response was unexplained pain (93.3%). Smoking was the most recognized risk factor in both groups: (82.8% for control; 84.1% for intervention) at T0. However, there was no significant change in T1 for the control group, but there was for the intervention group (p<0.001), the highest identification was smoking cigarettes (96.5%). Too scared was the largest barrier to seeking medical help by students in the control group at T0 (63.0%) and T1 (62.8%). However, there were no significant changes in all barriers in this group. Otherwise, being too embarrassed (60.2%) was the largest barrier to seeking medical help for students in the intervention group at T0 and too scared (58.6%) at T1. Although there were reductions in all barriers, significant differences were found in six of ten only (p<0.001). Conclusion: The intervention was effective in improving students' awareness of cancer symptoms, warning signs (p<0.001), and risk factors (p<0.001 reduced the most addressed barriers to seeking medical help (p<0.001) in comparison to the control group. The Ministry of Education in Oman could integrate awareness of cancer within the curriculum, and more interventions are needed on the sociological part to overcome the barriers that interfere with seeking medical help.

Keywords: adolescents, awareness, cancer, education, intervention, student

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Authors: Jasaswini Mishra, Ashim K. Dey

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This paper aims to investigate the group interaction effects of laterally loaded pile groups driven into a medium dense sand layer in submerged state. Static lateral load tests were carried out on pile groups consisting of varying number of piles and at different spacings. The test setup consists of a load cell (500 kg capacity) and an LVDT (50 mm) to measure the load and pile head deflection respectively. The piles were extensively instrumented with strain gauges so as to study the variation of soil resistance within the group. The bending moments at various depths were calculated from strain gauge data and these curves were fitted using a higher order polynomial in order to get 'p-y' curves. A comparative study between a single pile and a pile under a group has also been done for a better understanding of the group effect. It is observed that average load per pile is significantly reduced relative to single pile and it decreases with increase in the number of piles in a pile group. The loss of efficiency of the piles in the group, commonly referred to as "shadowing" effect, has been expressed by the use of a 'p-multiplier'. Leading rows carries greater amount of load when compared with the trailing rows. The variations of bending moment with depth for different rows of pile within a group and different spacing have been analyzed and compared with that of a single pile. p multipliers within different rows in a pile group were evaluated from the experimental study.

Keywords: group action, laterally loaded piles, p-multiplier, strain gauge

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Authors: Liudmila Garzanova, Lidia Ananyeva, Olga Koneva, Olga Ovsyannikova, Oxana Desinova, Mayya Starovoytova, Rushana Shayahmetova, Anna Khelkovskaya-Sergeeva

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Objectives. The age of the disease onset could have an impact on the effect of therapy in systemic sclerosis(SSc). Late-age onset in SSc could have a more severe course of the disease and worse clinical effects on therapy. The aim of our study was to evaluate changes in skin fibrosis on rituximab(RTX) therapy in patients with SSc and different ages of the disease onset. Methods. 151 patients with SSc were included in this study. Patients were divided into groups depending on the age of the disease onset: group 1 - younger than 30 years (40 patients(26%), group 2 - 31-59 years (90 patients(60%) and group 3 – more than 60 years (21 patients(14%). The mean follow-up period was 13±2.3month. The mean age was 48±13years, female-83% of patients, and the diffuse cutaneous subset of the disease had 52% of patients. The mean disease duration was 6.4±5years. The cumulative mean dose of RTX was 1.5±0.6grams. Patients received RTX as a therapy for interstitial lung disease. All patients received prednisone at a dose of 11.6±4.8mg/day, immunosuppressants received 48% of them. The results at baseline and at the end of the follow-up are presented in the form of mean values. Results. There was a significant decrease of modified Rodnan skin score(mRss) in all groups: in group 1 - from 10.2±8 to 7.7±6.5(p=0.01); in group 2 - from 9±7.2 to 6.2±4.7(p=0.0001); in group 3 - from 20.5±14.1 to 10.8±9.4(p=0.001). There was a significant decrease of the activity index (EScSG-AI): in group 1 from 2.5±1.8 to 1.3±1.1; in group 2 – from 3.2±1.6 to 1.5±1.2; in group 3 – from 4.2±2.1 to 1.3±1. Conclusion. There was a significant improvement in skin fibrosis in a year after initiation of RTX therapy regardless of the age of the disease onset. The improvement was more pronounced in the group with late-age onset of the disease, but these data require further investigations.

Keywords: skin fibrosis, systemic sclerosis, rituximab, disease onset

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Authors: Gurjeet Khurana, Surender Singh, Poonam Arora, Praveendra K. Sachan

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Introduction: Post-operative quality of recovery is the key outcome in the perspective of anesthesiologist. It is directly related to patient satisfaction. This is unsurprising, considering most aspects of a poor quality recovery after surgery will impair satisfaction with care. This study was thus undertaken to evaluate effects of Dexamethasone and Lignocaine on Quality of Recovery using QoR- 40 questionnaire and compare their effects. Material and methods: After obtaining the ethical committee approval and written informed consent, 67 patients of 18-60 years, ASA grade I and II scheduled for elective laparoscopic cholecystectomy were randomly allocated into two groups. Group I of 34 patients received 2mg/kg lignocaine diluted to 10ml with normal saline. Group 2 of 33 patients received 0.1 mg/kg I/V Dexamethasone diluted to 10ml with normal saline. QoR-40 was assessed on pre-operative day, and again QoR-40 was assessed at 24 hr post-operative day-1. Postoperative pain scores, nausea and vomiting and shoulder pain were secondary outcomes. Results: The Global QoR-40 was more than 180 at 24 hr in both the groups. The Dexamethasone group had higher Global QoR-40 than lignocaine group 187.94 v/s 182.85. Amongst dimensions of QoR-40 Dexamethasone had statistically better physical comfort, physical independence, and pain relief as compared to Lignocaine. Positive items had excellent responses in Dexamethasone group. Headache, backache and sore throat were also less severe in Dexamethasone group as compared to Lignocaine group. Dexamethasone group had lower VAS compared to lignocaine group. Similarly, there was less fentanyl consumption in dexamethasone group (364.08 ± 127.31) in postoperative period when compared to the lignocaine group (412.31 ± 147.8). Group receiving dexamethasone had 36% increase in appetite compared to lignocaine group (17.6%), which facilitated early oral feeding. Frequency of PONV was less in group-2 at different time interval as compared to group 1. Total episode of PONV were 18 in group 1 and 7 in group 2. Statistically significant difference was seen among two groups (p value= 0.007). Use of antiemetic was more in group 1 as compared to group 2 at all the times, though it was not statistically significant at different time intervals. Antiemetics were administered to 18 patients in group 1 as compared to 5 patients in group 2 postoperatively. Statistically significant difference (p value= 0.011) was seen in total antiemetic consumption. Conclusion: Our study demonstrated that pre-operative administration of a single dose of dexamethasone enhanced the quality of recovery after laparoscopic cholecystectomy as compared to Lignocaine bolus dose.

Keywords: dexamethasone, lignocaine, QoR-40 questionnaire, quality of recovery

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Authors: Nimit Soonsan

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Hotel image is a key business issue in today’s hotel market and has been increasingly been recognized as a valuable and inimitable source of competitive advantage by many hotel. The current study attempted to develop and test a relationship of hotel image, overall satisfaction, and future behavior. Based on the above concepts, this paper hypothesizes the correlations among four constructs, namely, hotel image and overall satisfaction as antecedents of future behavior that positive word-of-mouth and intention to revisit. This study surveyed for a sample of 244 international customers staying budget hotel in Phuket, Thailand and using a structural equation modeling identified relationship between hotel image, overall satisfaction and future behavior. The major finding of structural equation modeling indicates that hotel image directly affects overall satisfaction and indirectly affects future behavior that positive word-of-mouth and intention to revisit. In addition, overall satisfaction had significant influence on future behavior that positive word-of-mouth and intention to revisit, and the mediating role of overall satisfaction is also confirmed in this study. Managerial implications are provided, limitations noted, and future research directions suggested.

Keywords: hotel image, satisfaction, word-of-mouth, revisit

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

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The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: neural network computing, continuous functions generating the input-output mapping, decreasing the training time, machines with big memories

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Authors: Maha Deif, Alaa Eldin Hassan, Eman Shaat, Nesrine Elazhary, Eman Magdy

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Background: Erythropoietin (EPO) is a hematopoietic factor with multiple protective effects. The aim of the present study was to investigate the potential effect of EPO administration on renal functions and hypoxia inducible factor 1-alpha (HIF-1a) in diabetic rat kidneys. Methodology: The current study was carried out on 40 male albino rats divided into four groups (n= 10 in each). Group I served as normal control, group II was the diabetic control, group III rats received EPO on the same day of diagnosis of diabetes mellitus (DM), while group IV received the first dose of EPO 2 weeks after the diagnosis of DM. Results: The results showed that EPO supplementation leads to a significant decrease in serum urea, urinary protein and creatinine clearance as well as a significant increase in renal HIF-1a in group III and IV rats compared to the diabetic control group (group II). However, fasting blood glucose was significantly decreased in group III as compared to the diabetic control group in the third week, but no significant difference was reported in the fourth week among groups II, III and IV. Conclusion: EPO administration leads to the improvement of renal functions and increased levels of HIF-1a in diabetic rats.

Keywords: erythropoietin, diabetic nephropathy, hypoxia-inducible factor1-alpha, renal functions

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Authors: Ashkan Shafee, Ahamd Fahimifar, Sajjad V. Maghvan

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Promotion of the Fiber Reinforced Concrete (FRC) as a construction material for civil engineering projects has invoked numerous researchers to investigate their mechanical behavior. Even though there is satisfactory information about the effects of fiber type and length, concrete mixture, casting type and other variables on the strength and deformability parameters of FRC, the numerical modeling of such materials still needs research attention. The focus of this study is to investigate the feasibility of Concrete Damaged Plasticity (CDP) model in prediction of Macro-synthetic FRC structures behavior. CDP model requires the tensile behavior of concrete to be well characterized. For this purpose, a series of uniaxial direct tension and four point bending tests were conducted on the notched specimens to define bilinear tension softening (post-peak tension stress-strain) behavior. With these parameters obtained, the flexural behavior of macro-synthetic FRC beams were modeled and the results showed a good agreement with the experimental measurements.

Keywords: concrete damaged plasticity, fiber reinforced concrete, finite element modeling, macro-synthetic fibers, uniaxial tensile test

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Authors: Dorota Galeza

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This paper argues that networks, such as the ECN and the American network, are affected by certain small events which are inherent to path dependence and preclude the full evolution towards efficiency. It is advocated that the American network is superior to the ECN in many respects due to its greater flexibility and longer history. This stems in particular from the creation of the American network, which was based on a small number of cases. Such structure encourages further changes and modifications which are not necessarily radical. The ECN, by contrast, was established by legislative action, which explains its rigid structure and resistance to change. It might be the case that the ECN is subject not so much to path dependence but to past dependence. It might have to be replaced, as happened to its predecessor. This paper is an attempt to transpose the superiority of the American network on to the ECN. It looks at concepts such as judicial cooperation, harmonization of procedure, peer review and regulatory impact assessments (RIAs), and dispute resolution procedures. The aim is to adopt these concepts into the EU setting without recourse to legal transplantation. The major difficulty is that many of these concepts have been tested only in the US and it is difficult to tell whether they could be modified to meet EU standards. Concepts such as judicial cooperation might be difficult due to different language traditions in EU member states. It is hoped that greater flexibility, as in the American network, would boost legitimacy and transparency.

Keywords: ECN, networks, regulation, competition

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Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula

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A functional model to mimic the functional correctness of a neural network compute accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of GCC compilers to the BF-16 datatype, which we addressed with a native BF-16 generator integrated into our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex neural network accelerator design by proposing a functional model-based scoreboard or software model using SystemC. The proposed functional model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT, bringing up micro-steps of execution.

Keywords: ISA, neural network, Brain Float-16, DUT

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Authors: Shankaran Sitarama

Abstract:

New Product Development (NPD) is invariably a team effort and involves effective teamwork. NPD team has members from different disciplines coming together and working through the different phases all the way from conceptual design phase till the production and product roll out. Creativity and Innovation are some of the key factors of successful NPD. Team members going through the different phases of NPD interact and work closely yet challenge each other during the design phases to brainstorm on ideas and later converge to work together. These two traits require the teams to have a divergent and a convergent thinking simultaneously. There needs to be a good balance. The team dynamics invariably result in conflicts among team members. While some amount of conflict (ideational conflict) is desirable in NPD teams to be creative as a group, relational conflicts (or discords among members) could be detrimental to teamwork. Team communication truly reflect these tensions and team dynamics. In this research, team communication (emails) between the members of the NPD teams is considered for analysis. The email communication is processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. The amount of communication (content and not frequency of communication) defines the interaction strength between the members. Social network adjacency matrix is thus obtained for the team. Standard social network analysis techniques based on the Adjacency Matrix (AM) and Dichotomized Adjacency Matrix (DAM) based on network density yield network graphs and network metrics like centrality. The social network graphs are then rendered for visual representation using a Metric Multi-Dimensional Scaling (MMDS) algorithm for node placements and arcs connecting the nodes (representing team members) are drawn. The distance of the nodes in the placement represents the tie-strength between the members. Stronger tie-strengths render nodes closer. Overall visual representation of the social network graph provides a clear picture of the team’s interactions. This research reveals four distinct patterns of team interaction that are clearly identifiable in the visual representation of the social network graph and have a clearly defined computational scheme. The four computational patterns of team interaction defined are Central Member Pattern (CMP), Subgroup and Aloof member Pattern (SAP), Isolate Member Pattern (IMP), and Pendant Member Pattern (PMP). Each of these patterns has a team dynamics implication in terms of the conflict level in the team. For instance, Isolate member pattern, clearly points to a near break-down in communication with the member and hence a possible high conflict level, whereas the subgroup or aloof member pattern points to a non-uniform information flow in the team and some moderate level of conflict. These pattern classifications of teams are then compared and correlated to the real level of conflict in the teams as indicated by the team members through an elaborate self-evaluation, team reflection, feedback form and results show a good correlation.

Keywords: team dynamics, team communication, team interactions, social network analysis, sna, new product development, latent semantic analysis, LSA, NPD teams

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Authors: Lopamudra Bakshi Basu

Abstract:

Transport is one of the most important characteristic features of Indian cities. The physical and societal requirements determine the selection of a particular transport system along with the uniqueness of road networks. Kolkata has a mixed traffic of which Paratransit system plays a crucial role. It is an indispensable transport system in Kolkata mainly because of its size and service flexibility which has led to a unique network character. The paratransit system, mainly the autorickshaws, is the most favoured mode of transport in the city. Its fast movement and comfortability make it a vital transport system of the city. Since the inception of the autorickshaws in Kolkata in 1981, this mode has gained popularity and presently serves nearly 80 to 90 percent of the total passenger trips. This employment generating mode of transport has increased its number rapidly affecting the city’s traffic. Minimal check on their growth by the authority has led to traffic snarls along many streets of Kolkata. Indiscipline behavior, violation of traffic rules and rash driving make situations even worse. The rise in the number and increasing popularity of the autorickshaws make it an interesting study area. Autorickshaws as a paratransit mode play its role as a leader or a follower. However, it is informal in its planning and operations, which makes it a problem area for the city. The entire research work deals with the growth and expansion of the number of vehicles and the routes within the city. The development of transport system has been interesting in the city, which has been studied. The growth of the paratransit modes in the city has been rapid. The network pattern of the paratransit mode within Kolkata has been analysed.

Keywords: growth, informal, network characteristics, paratransit, service flexibility

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Authors: Edward P. Guillen, A. Karina Martinez Barliza

Abstract:

Powerline Communications (PLC) as last mile solution to provide communication services, has the advantage of transmitting over channels already used for electrical distribution. However these channels have been not designed with this purpose, for that reason telecommunication companies in Colombia want to know how good would be using PLC in costs and network performance in comparison to cable modem or DSL. This paper analyzes PLC throughput for residential complex scenarios using a PLC network scenarios and some statistical results are shown.

Keywords: home network, power line communication, throughput analysis, power factor, cost, last mile solution

Procedia PDF Downloads 266

Authors: Johnson O. Adeogo, Ayodele S. Oluwole, O. Akinsanmi, Olawale J. Olaluyi

Abstract:

In this 5G network, very high traffic density in densely populated areas, most especially in densely populated areas, is one of the key requirements. Radiation reduction becomes one of the major concerns to secure the future life of mobile network users in ultra-dense network areas using an improved coordinated multipoint technology. Coordinated Multi-Point (CoMP) is based on transmission and/or reception at multiple separated points with improved coordination among them to actively manage the interference for the users. Small cells have two major objectives: one, they provide good coverage and/or performance. Network users can maintain a good quality signal network by directly connecting to the cell. Two is using CoMP, which involves the use of multiple base stations (MBS) to cooperate by transmitting and/or receiving at the same time in order to reduce the possibility of electromagnetic radiation increase. Therefore, the influence of the screen guard with rubber condom on the mobile transceivers as one major piece of equipment radiating electromagnetic radiation was investigated by mobile network users amidst ultra-dense networks in 5g. The results were compared with the same mobile transceivers without screen guards and rubber condoms under the same network conditions. The 5 cm distance from the mobile transceivers was measured with the help of a ruler, and the intensity of Radio Frequency (RF) radiation was measured using an RF meter. The results show that the intensity of radiation from various mobile transceivers without screen guides and condoms was higher than the mobile transceivers with screen guides and condoms when call conversation was on at both ends.

Keywords: ultra-dense networks, mobile network users, 5g, coordinated multi-point.

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Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

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Authors: Harsh Sadawarti, Kamal Malik

Abstract:

Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.

Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe

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Authors: Teklu Urgessa, Joong Seek Lee

Abstract:

Social media is becoming the primary choice of activists to make their voices heard. This fact is coupled by two main reasons. The first reason is the emergence web 2.0, which gave the users opportunity to become content creators than passive recipients. Secondly the control of the mainstream mass media outlets by the governments and individuals with their political and economic interests. This paper aimed at exploring twitter data of network actors talking about the marathon silver medalists on Rio2016, who showed solidarity with the Oromo protesters in Ethiopia on the marathon race finish line when he won silver. The aim is to discover important insight using social network analysis and mining. The hashtag #FeyisaLelisa was used for Twitter network search. The actors’ network was visualized and analyzed. It showed the central influencers during first 10 days in August, were international media outlets while it was changed to individual activist in September. The degree distribution of the network is scale free where the frequency of degrees decay by power low. Text mining was also used to arrive at meaningful themes from tweet corpus about the event selected for analysis. The semantic network indicated important clusters of concepts (15) that provided different insight regarding the why, who, where, how of the situation related to the event. The sentiments of the words in the tweets were also analyzed and indicated that 95% of the opinions in the tweets were either positive or neutral. Overall, the finding showed that Olympic stage protest of the marathoner brought the issue of Oromo protest to the global stage. The new research framework is proposed based for event-based social network analysis and mining based on the practical procedures followed in this research for event-based social media sense making.

Keywords: human rights, Olympics, social media, network analysis, social network ming

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Authors: Vivek Ku, A. K. Janmeja, D. Aggarwal, R. Gupta

Abstract:

Purpose: Pulmonary rehabilitation plays a key role in management of chronic lung diseases. However, pulmonary rehabilitation is an underused modality in the management of interstitial lung disease (ILD). This is because limited information is available in literature and no data is available from India on this issue so far. The study was carried out to evaluate the role of pulmonary rehabilitation on respiratory parameters in ILD patients. Methods: The present study was a prospective randomized non-blind case control study. Total of 40 ILD patients were randomized into 2 groups of 20 patients each viz ‘pulmonary rehabilitation group’ and ‘control group’. Pulmonary rehabilitation group underwent 8 weeks pulmonary rehabilitation (PR) along with medical management as per guidelines and the control group was advised only medical management. Results: Mean age in case group was 59.15 ± 10.39 years and in control group was 62.10 ± 14.54 years. The case and the control groups were matched for age and sex. Mean MRC grading at the end of 8 weeks showed significant improvement in the case group as compared to control group (p= 0.011 vs p = 0.655). Similarly, mean St. George Respiratory Questionnaire (SGRQ) score also showed significant improvement in pulmonary rehabilitation group at the end of the study (p= 0.001 vs p= 0.492). However, FEV1 and FVC had no significant change in the case and control group. Similarly, blood gases also did not show any significant difference in the group. Conclusion: Pulmonary rehabilitation improves breathlessness and thereby improves quality of life in the patients suffering from ILD. However, the pulmonary function values and blood gases are unaffected by pulmonary rehabilitation. Clinical Implications: Further large scale multicentre study is needed to ascertain the association.

Keywords: ILD, pulmonary rehabilitation, quality of life, pulmonary functions

Procedia PDF Downloads 270